This article was written in collaboration with Edelbridge Alpha and summarizes a conversation Daniel Koss and I had about memory that lasted nearly two hours. You can also read it on the their Substack.
Author: Daniel Koss in collaboration with Damnang.
Many of you will already know Damnang from his writing on X. I recently sat down with him for a conversation about one of the most important parts of the AI infrastructure stack: memory.
Damnang is a semiconductor engineer working in Silicon Valley. His background is in digital chip design, and he follows memory and the broader semiconductor industry closely.
We started with the basics. What is memory? Why do we need different types? And why does AI change the equation?
Then we moved to the questions that matter to investors. Can memory prices keep rising? Does more capacity inevitably mean another downcycle? How much power does NVIDIA have over its suppliers? And how should we think about the different memory companies?
What I found most valuable was where his engineering perspective challenged my investing perspective. He sees important technical advantages at Samsung, understands the appeal of SK hynix, and ultimately chooses Micron for his own circumstances.
To respect Damnang’s anonymity, this interview is being published in text only. No audio or video accompanies this article.
Below are my key takeaways, a company-by-company summary, and the edited interview.
Editorial note: This is an edited interview, not a verbatim transcript. The preliminary getting-to-know-you conversation, filler, repeated phrases, and off-topic digressions have been removed. Questions and answers have been tightened for readability, and clear transcription errors have been corrected. Several unclear figures and unverified anecdotes have been omitted. Forecasts, estimates, and industry commentary remain the speakers’ opinions at the time of the conversation. The takeaways and closing section are my interpretation, separate from Damnang’s answers.
